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   系統號碼942773
   書刊名Machine learning and optimization techniques for automotive cyber-physical systems [electronic resource] /
   主要著者edited by Vipin Kumar Kukkala, Sudeep Pasricha.
   其他著者Kukkala, Vipin Kumar.;Pasricha, Sudeep.
   出版項Cham : Imprint: Springer, 2023.
   索書號TK7895.E42M33 2023
   ISBN9783031280160
   標題Cooperating objects (Computer systems)
Machine learning.
Automated vehicles.
Embedded Systems.
Electronics Design and Verification.
Cyber-Physical Systems.
   電子資源https://doi.org/10.1007/978-3-031-28016-0
   
    
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內容簡介This book provides comprehensive coverage of various solutions that address issues related to real-time performance, security, and robustness in emerging automotive platforms. The authors discuss recent advances towards the goal of enabling reliable, secure, and robust, time-critical automotive cyber-physical systems, using advanced optimization and machine learning techniques. The focus is on presenting state-of-the-art solutions to various challenges including real-time data scheduling, secure communication within and outside the vehicle, tolerance to faults, optimizing the use of resource-constrained automotive ECUs, intrusion detection, and developing robust perception and control techniques for increasingly autonomous vehicles. The book describes state-of-the-art solutions to design secure, robust, and time-critical automotive systems; Various approaches are discussed that will impact the design of emerging autonomous vehicle systems; The content is relevant to researchers and industry practitioners interested in future automotive platforms.

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